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Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda

Aturinde, Augustus LU ; Rose, Nakasi ; Farnaghi, Mahdi LU ; Maiga, Gilbert ; Pilesjö, Petter LU and Mansourian, Ali LU (2019) In BMC Medical Informatics and Decision Making 19(1). p.215-215
Abstract

BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.

METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the... (More)

BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.

METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.

RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.

CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Spatially-enabled health registry, SDI, RESTful web services, Spatial epidemiology, Mobile GIS, Uganda
in
BMC Medical Informatics and Decision Making
volume
19
issue
1
pages
215 - 215
publisher
BioMed Central
external identifiers
  • scopus:85074720866
  • pmid:31703685
ISSN
1472-6947
DOI
10.1186/s12911-019-0949-y
language
English
LU publication?
yes
id
0a271250-d766-45c6-9bf6-1037bdf3ded5
date added to LUP
2019-11-15 10:54:06
date last changed
2020-01-13 02:31:28
@article{0a271250-d766-45c6-9bf6-1037bdf3ded5,
  abstract     = {<p>BACKGROUND: Spatial epidemiological analyses primarily depend on spatially-indexed medical records. Some countries have devised ways of capturing patient-specific spatial details using ZIP codes, postcodes or personal numbers, which are geocoded. However, for most resource-constrained African countries, the absence of a means to capture patient resident location as well as inexistence of spatial data infrastructures makes capturing of patient-level spatial data unattainable.</p><p>METHODS: This paper proposes and demonstrates a creative low-cost solution to address the issue. The solution is based on using interoperable web services to capture fine-scale locational information from existing "spatial data pools" and link them to the patients' information.</p><p>RESULTS: Based on a case study in Uganda, the paper presents the idea and develops a prototype for a spatially-enabled health registry system that allows for fine-level spatial epidemiological analyses.</p><p>CONCLUSION: It has been shown and discussed that the proposed solution is feasible for implementation and the collected spatially-indexed data can be used in spatial epidemiological analyses to identify hotspot areas with elevated disease incidence rates, link health outcomes to environmental exposures, and generally improve healthcare planning and provisioning.</p>},
  author       = {Aturinde, Augustus and Rose, Nakasi and Farnaghi, Mahdi and Maiga, Gilbert and Pilesjö, Petter and Mansourian, Ali},
  issn         = {1472-6947},
  language     = {eng},
  month        = {11},
  number       = {1},
  pages        = {215--215},
  publisher    = {BioMed Central},
  series       = {BMC Medical Informatics and Decision Making},
  title        = {Establishing spatially-enabled health registry systems using implicit spatial data pools: case study - Uganda},
  url          = {http://dx.doi.org/10.1186/s12911-019-0949-y},
  doi          = {10.1186/s12911-019-0949-y},
  volume       = {19},
  year         = {2019},
}